E. Gai

633 citations
27 papers · 434 indexed · h-index 10

E. Gai

26 papers receiving 369 citations

Peers

E. Gai
Comparison fields: 5 of 53
  • Statistics, Probability and Uncertainty 78
  • Aerospace Engineering 232
  • Control and Systems Engineering 180
  • Oceanography 54
  • Artificial Intelligence 141
Replace Bor‐Chin Chang with:
Bor‐Chin Chang United States
Mark A. Sturza Japan
R. Moose United States
Hari B. Hablani United States
James D. Turner United States
Barton J. Bacon United States
A. Barraud France
K. Birmiwal United States
Xiuqiang Jiang China
Sherry E. Hammel United States
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Countries citing papers authored by E. Gai

Since Specialization
Citations

This map shows the geographic impact of E. Gai's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by E. Gai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites E. Gai more than expected).

Fields of papers citing papers by E. Gai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by E. Gai. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by E. Gai. The network helps show where E. Gai may publish in the future.

Co-authorship network

The 15 scholars most cited alongside E. Gai, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with E. Gai Line = papers co-authored together E. Gai links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20241
2 20026
3 19892
4 19842
5 198455
6 19833
7 19832
8 19831
9 198321
10
Inflight parity vector compensation for FDI
19824
11 19812
12 19810
13 198110
14 19804
15 197913
16 19782
17 197719
18 197643
19 197611
20
Psychophysical Models for Signal Detection with Time Varying Uncertainty
19753

About E. Gai

E. Gai is a scholar working on Statistics, Probability and Uncertainty, Software, Health Informatics, Control and Systems Engineering and Aerospace Engineering, having authored 27 papers that have together received 434 indexed citations. Recurring topics across this work include Fault Detection and Control Systems (11 papers), Inertial Sensor and Navigation (7 papers), Target Tracking and Data Fusion in Sensor Networks (6 papers), Astronomical Observations and Instrumentation (4 papers), Risk and Safety Analysis (4 papers), Reliability and Maintenance Optimization (4 papers), Software Reliability and Analysis Research (3 papers) and Aerospace and Aviation Technology (3 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (78 citations), Aerospace Engineering (232 citations), Control and Systems Engineering (180 citations), Oceanography (54 citations) and Artificial Intelligence (141 citations). E. Gai has collaborated with scholars based in United States and China. Frequent co-authors include Kevin C. Daly, Renwick E. Curry, Robert L. White, John Deyst, David C. Nagel, Bruce K. Walker, Steven Hall, John Harrison, Mukund Desai and Steven R. Hall. Their work appears in journals such as IEEE Transactions on Aerospace and Electronic Systems, Journal of Guidance Control and Dynamics, Journal of Aircraft, IEEE Transactions on Automatic Control and SAE technical papers on CD-ROM/SAE technical paper series.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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